Orthogonal Frequency Division Multiplexing (OFDM) provides good data throughput for a given bandwidth and is therefore widely employed for wireless systems. OFDM has been adopted by various wireless standards such as IEEE 802.11a, 802.16, ETSI HIPERLAN/2 as well as digital video broadcasting (DVB).
Channel estimation is of critical importance to OFDM because the channel varies across the frequency domain sub-carriers and also across OFDM symbols in time.
Channel decoders (e.g., turbo or Low-Density Parity Check (LDPC) decoders) need inputs to be able to properly decode the received coded waveform and one type of input is the Logarithm of the Likelihood Ratio (LLR). A standard means of computing LLRs given a channel estimate in an OFDM system is to generate the LLRs using the channel estimates based on a flat Rayleigh fading assumption (because an OFDM channel estimate on a particular subcarrier looks like it is flat Rayleigh faded). However, such techniques assume correct channel estimates and will not work well when there is significant channel estimation error.
Techniques do exist for accounting for channel estimation error when computing LLRs in OFDM systems. For example, in M. M. Wang, W. Xiao, & T. Brown, “Soft Decision Metric Generation for QAM With Channel Estimation Error,” IEEE Transactions On Communications, Vol. 50, No. 7 (July 2002), a system is described which considers channel estimation Mean Square Error (MSE) when computing LLRs in OFDM. However, the disclosed techniques do not consider the multi-user aspect, and do not consider the frequency-domain channel estimation MSE, which is not uniform across frequency. Further, such techniques have not considered LLR generation for antenna combining algorithms such as Minimum Mean Square Error (MMSE), successive cancellation, and maximum likelihood detection (which is also known as joint detection).
Therefore, such systems have been limited to a single data source and a single receiving antenna. Other techniques, for example LLR generation for LDPC codes in Multiple-Input/Multiple-Output (MIMO) OFDM, also neglect channel estimation error, or otherwise neglect the fact that channel estimation error can vary greatly across frequency, and therefore such techniques will not work well for cases having significant channel estimation error.
Further, the performance of turbo-coded or LDPC-coded OFDM channels can be seriously degraded when the channel estimation error is not accounted for especially for higher order Quadrature Amplitude Modulations (QAM) such as 16-QAM and 64-QAM.
Therefore what is needed is an apparatus and method for computing LLRs for single or multiple data streams and multiple antenna combining techniques while accounting for channel estimation error.